github-repo-governance
skillRepository governance covers policies, standards, and controls for managing GitHub repositories effectively. This skill includes repository settings, access controls, branch protection, security polic
apm::install
apm install @amnadtaowsoam/github-repo-governanceapm::skill.md
---
id: SKL-github-GITHUBREPOGOVERNANCE
name: Github Repo Governance
description: Repository governance covers policies, standards, and controls for managing
GitHub repositories effectively. This skill includes repository settings, access
controls, branch protection, security polic
version: 1.0.0
status: active
owner: '@cerebra-team'
last_updated: '2026-02-22'
category: Backend
tags:
- api
- backend
- server
- database
stack:
- Python
- Node.js
- REST API
- GraphQL
difficulty: Intermediate
---
# Github Repo Governance
## Skill Profile
*(Select at least one profile to enable specific modules)*
- [ ] **DevOps**
- [x] **Backend**
- [ ] **Frontend**
- [ ] **AI-RAG**
- [ ] **Security Critical**
## Overview
Repository governance covers policies, standards, and controls for managing GitHub repositories effectively. This skill includes repository settings, access controls, branch protection, security policies, and best practices for maintaining healthy and secure repositories.
## Why This Matters
- **Security**: Protect repositories from unauthorized access and changes
- **Compliance**: Ensure adherence to organizational policies and standards
- **Quality**: Enforce code quality and review standards
- **Accountability**: Maintain clear ownership and responsibility
---
## Core Concepts & Rules
### 1. Core Principles
- Follow established patterns and conventions
- Maintain consistency across codebase
- Document decisions and trade-offs
### 2. Implementation Guidelines
- Start with the simplest viable solution
- Iterate based on feedback and requirements
- Test thoroughly before deployment
## Inputs / Outputs / Contracts
* **Inputs**:
- Governance requirements and policies
- Team structure and permissions
- Security requirements
- Compliance standards
* **Entry Conditions**:
- Organization or repository exists
- Team structure defined
- Governance requirements documented
- Security policies defined
* **Outputs**:
- Configured repository settings
- Access control policies implemented
- Branch protection rules configured
- Security policies enabled
* **Artifacts Required (Deliverables)**:
- Repository configuration
- CODEOWNERS file
- Branch protection rules
- Security policies
- Issue and PR templates
* **Acceptance Evidence**:
- Repository settings configured
- Access controls implemented
- Branch protection active
- Security scans enabled
- Templates available
* **Success Criteria**:
- Policy compliance 100%
- Security incidents 0 per month
- Unauthorized access 0
- Template usage > 90%
## Skill Composition
* **Depends on**: [skill-github-code-review](./github-code-review/), [skill-github-pr-lifecycle](./github-pr-lifecycle/), [skill-github-security-triage](./github-security-triage/)
* **Compatible with**: [skill-github-issue-triage](./github-issue-triage/), [skill-github-workflow-ops](./github-workflow-ops/)
* **Conflicts with**: Over-permissive access or no branch protection
* **Related Skills**: [skill-security-baseline](../../64-meta-standards/security-baseline-controls/), [skill-api-style-guide](../../64-meta-standards/api-style-guide/)
---
## Quick Start / Implementation Example
1. Review requirements and constraints
2. Set up development environment
3. Implement core functionality following patterns
4. Write tests for critical paths
5. Run tests and fix issues
6. Document any deviations or decisions
```python
# Example implementation following best practices
def example_function():
# Your implementation here
pass
```
## Assumptions / Constraints / Non-goals
* **Assumptions**:
- Development environment is properly configured
- Required dependencies are available
- Team has basic understanding of domain
* **Constraints**:
- Must follow existing codebase conventions
- Time and resource limitations
- Compatibility requirements
* **Non-goals**:
- This skill does not cover edge cases outside scope
- Not a replacement for formal training
## Compatibility & Prerequisites
* **Supported Versions**:
- Python 3.8+
- Node.js 16+
- Modern browsers (Chrome, Firefox, Safari, Edge)
* **Required AI Tools**:
- Code editor (VS Code recommended)
- Testing framework appropriate for language
- Version control (Git)
* **Dependencies**:
- Language-specific package manager
- Build tools
- Testing libraries
* **Environment Setup**:
- `.env.example` keys: `API_KEY`, `DATABASE_URL` (no values)
## Test Scenario Matrix (QA Strategy)
| Type | Focus Area | Required Scenarios / Mocks |
| :--- | :--- | :--- |
| **Unit** | Core Logic | Must cover primary logic and at least 3 edge/error cases. Target minimum 80% coverage |
| **Integration** | DB / API | All external API calls or database connections must be mocked during unit tests |
| **E2E** | User Journey | Critical user flows to test |
| **Performance** | Latency / Load | Benchmark requirements |
| **Security** | Vuln / Auth | SAST/DAST or dependency audit |
| **Frontend** | UX / A11y | Accessibility checklist (WCAG), Performance Budget (Lighthouse score) |
## Technical Guardrails & Security Threat Model
### 1. Security & Privacy (Threat Model)
* **Top Threats**: Injection attacks, authentication bypass, data exposure
- [ ] **Data Handling**: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
- [ ] **Secrets Management**: No hardcoded API keys. Use Env Vars/Secrets Manager
- [ ] **Authorization**: Validate user permissions before state changes
### 2. Performance & Resources
- [ ] **Execution Efficiency**: Consider time complexity for algorithms
- [ ] **Memory Management**: Use streams/pagination for large data
- [ ] **Resource Cleanup**: Close DB connections/file handlers in finally blocks
### 3. Architecture & Scalability
- [ ] **Design Pattern**: Follow SOLID principles, use Dependency Injection
- [ ] **Modularity**: Decouple logic from UI/Frameworks
### 4. Observability & Reliability
- [ ] **Logging Standards**: Structured JSON, include trace IDs `request_id`
- [ ] **Metrics**: Track `error_rate`, `latency`, `queue_depth`
- [ ] **Error Handling**: Standardized error codes, no bare except
- [ ] **Observability Artifacts**:
- **Log Fields**: timestamp, level, message, request_id
- **Metrics**: request_count, error_count, response_time
- **Dashboards/Alerts**: High Error Rate > 5%
## Agent Directives & Error Recovery
*(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)*
- **Thinking Process**: Analyze root cause before fixing. Do not brute-force.
- **Fallback Strategy**: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
- **Self-Review**: Check against Guardrails & Anti-patterns before finalizing.
- **Output Constraints**: Output ONLY the modified code block. Do not explain unless asked.
## Definition of Done (DoD) Checklist
- [ ] Tests passed + coverage met
- [ ] Lint/Typecheck passed
- [ ] Logging/Metrics/Trace implemented
- [ ] Security checks passed
- [ ] Documentation/Changelog updated
- [ ] Accessibility/Performance requirements met (if frontend)
## Anti-patterns / Pitfalls
* ⛔ **Don't**: Log PII, catch-all exception, N+1 queries
* ⚠️ **Watch out for**: Common symptoms and quick fixes
* 💡 **Instead**: Use proper error handling, pagination, and logging
## Reference Links & Examples
* Internal documentation and examples
* Official documentation and best practices
* Community resources and discussions
## Versioning & Changelog
* **Version**: 1.0.0
* **Changelog**:
- 2026-02-22: Initial version with complete template structure